Senior Engineer - GenAI Engineering

Job Summary

GE Vernova is embracing cutting‑edge technologies to streamline operations, improve customer experiences, and drive growth. As part of this vision, we are building a dedicated team to leverage Generative AI and redefine how we engage with our industry. The team will automate prompting, develop a framework for prompting across use cases to maximize reuse and sharing across businesses.

This position offers a great opportunity to work at the intersection of advanced technology and the traditional industry, making a tangible impact on our business processes.

• Collaborate with domain experts to understand business needs and translate them into clear and effective LLM prompts.
• Develop, test, and refine prompts for a variety of use cases, ensuring high accuracy and relevance in generated outputs.
• Work closely with software developers to integrate LLM solutions into existing or new applications.
• Contribute to the development of a scalable framework for prompt engineering, promoting reuse and knowledge sharing across different business units.
• Assist in gathering and analyzing user feedback to continually improve prompt effectiveness.
• Stay up‑to‑date with advancements in LLM technology and contribute to strategic decisions on tool and platform selection.
• Document prompt engineering processes, best practices, and use case outcomes to build a comprehensive knowledge base.

• 5+ years of relevant experience and a Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, AI Engineering, or related fields.
• 3+ years of experience with prompt engineering and familiarity with tools such as OpenAI’s GPT models, Hugging Face, etc.
• 3+ years of experience with Python or other programming languages commonly used in AI/ML development.
• Strong problem‑solving skills and attention to detail.
• Excellent communication skills, with the ability to articulate complex technical concepts to non‑technical stakeholders.
• Ability to work collaboratively in a team environment and adapt to changing project requirements.

Must be willing to work out of an office located in Niskayuna, NY or Cambridge, MA. For Cambridge, MA based resources, this position includes a required three‑month (hybrid) onboarding residency at the GE Vernova Advanced Research Center in Niskayuna, NY. This immersive program allows senior talent to establish a strong technical foundation, collaborate with our premier scientists and engineers, and align with our mission to lead the energy transition.

Travel, housing, and living stipend provided.

• Master’s or PhD degree in Computer Science, Engineering, Data Science, or related field.
• Experience with machine learning frameworks (e.g., PyTorch) and data processing libraries (e.g., Pandas, Num Py).
• Previous experience or internships involving NLP or machine learning projects.
• Familiarity with version control systems like Git.
• Understanding of traditional industry operations and challenges.

Pay range for this position is between $ and $. The Company pays a geographic differential of 110%, 120% or 130% of salary in certain areas. Bonus eligibility: discretionary annual bonus. Benefits include medical, dental, vision, and prescription drug coverage; access to Health Coach from GE Vernova, a 24/7 nurse‑based resource; access to the Employee Assistance Program; retirement benefits with the GE Vernova Retirement Savings Plan, tax‑advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions;

access to Fidelity resources and financial planning consultants; tuition assistance; adoption assistance; paid parental leave; disability benefits; life insurance; 12 paid holidays; and permissive time off.

GE Vernova is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law. GE Vernova will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).